In recent years, the number of channels selectable by a user is spectacularly increased, as versatile TV viewing conditions such as cable TV broadcasting, satellite TV broadcasting, and digital TV broadcasting and IP (Internet Protocol) broadcasting thereof are available as well as conventional TV broadcasting. Under the above circumstances, the user may find it difficult to choose a program most suitable for him or her by zapping.
In order to solve the above drawback, there is known a method comprising: collecting information on programs selected by a user; and ranking the programs to automatically determine a program of a high general preference and to recommend the program to the user.
The above method enables to extract a program of a high general preference. However, not all the users have a general preference. Accordingly, it is impossible to recommend programs most suitable to the users individually, and a cumbersome operation is required for the users to retrieve programs of their preferences by themselves.
In view of the above, there is disclosed a method comprising: storing program selecting statuses of users in the past; administering the program selecting statuses in a server; comparing the program selecting statuses with respect to each of the users; defining the users having similar program selecting statuses as a group; and introducing a recommended program to the users based on the program selecting statuses in the group (see e.g. patent document 1).
There is also disclosed a method comprising: acquiring and calculating user information including program viewing log information, device manipulation log information relating to contents recording/reproducing, and user attribute information from multiple users; sorting the users into user groups according to grouping methods; and creating statistics information on a specific user group to introduce a recommended program to the users (see e.g. patent document 2).
In both of the methods, it is possible to extract a recommended program for users in a group by: collecting enormous viewing log information on the users; and grouping the users having identical preferences by a so-called collaborative filtering. The methods enables to provide a system advantageous to the users, without requesting the users a cumbersome operation to select programs of their preferences.
However, in the case where the above methods are used in the following condition, recommended program information provided by the above methods may be completely useless.
As one case, there is a program viewed by most of the users such as a sports program to be broadcast once in several years, or a music program to be broadcast once a year, irrespective of preferences of individual users. In this case, even if the users are grouped according to preference patterns, substantially an identical recommended program is extracted in any of the groups. In this condition, the grouping according to preference patterns of users is useless. A program which is expected to be viewed by most of the users can be easily selected by the users themselves, without using a system for extracting a recommended program. In this sense, the system is useless.
As another case, it is impossible to recommend a specific news or a specific scene in a program such as a news program. Even if a specific program is recommended, it is impossible for the users to determine which scene in the program is recommended. Consequently, the users are required to view the entirety of the program to determine the scene of their preference, which is time consuming.    Patent document 1: JP 2001-298677A    Patent document 2: JP2005-33600A